class_docstr: Deep feature extractor.
  
  Extracts the deep (appearance) features from the input regions.
code: def __init__(self) -> None:
      super().__init__()
  
      self.encoder, _ = clip.load("ViT-B/16")
      self.transform = Normalize(
          mean=(0.48145466, 0.4578275, 0.40821073),
          std=(0.26862954, 0.26130258, 0.27577711),
      )
  
imports: from __future__ import annotations
  from enum import Enum
  import torch
  from torch import Tensor, nn
  from torchvision.models.detection import KeypointRCNN_ResNet50_FPN_Weights, keypointrcnn_resnet50_fpn
  from torchvision.models.detection.roi_heads import keypointrcnn_inference
  from torchvision.ops import roi_align
  from torchvision.transforms import Normalize
  from anomalib.models.ai_vad.clip import clip
label_desc: Use image node_id 1 to create a new DeepExtractor object from inherited base classes: nn with example: obj = DeepExtractor()